基于改进灰狼算法的DG接入配电网反时限过电流保护定值优化

反时限过电流保护在含分布式电源的配电网中应用广泛,但其定值整定大多依赖工程经验,限制了实际的工程应用。为此,提出一种基于改进灰狼算法(GWO)的DG接入配电网反时限过电流保护定值优化方法,在保护动作特性方程和对保护灵敏性、速度性、选择性要求的基础上建立优化模型。为克服灰狼算法容易早熟、收敛精度低等缺陷,在保留可调参数少这一优势的前提下,引入了佳点集初始化、收敛因子指数衰减、变异和启发式参数确定这4种策略对灰狼算法做了改进。仿真算例验证了所提模型在两相和三相故障下的可行性与优越性,并探讨了时间级差对整定的影响、将来算法优化和工程应用的方向,为大规模DG接入配电网的保护定值优化问题提供了研究思路。

Optimal setting method of inverse time over-current protection for a distribution network based on the improved grey wolf optimization

Inverse time overcurrent protection is widely used in distribution networks with distributed power sources, but its setting mostly relies on engineering experience, which limits practical engineering application. Thus an optimization method for inverse-time overcurrent protection settings for DG access to distribution networks based on the improved Gray Wolf Algorithm (GWO) is proposed. This is based on the protection action characteristic equation and the requirements for protection sensitivity, speed, and selectivity. In order to overcome the shortcomings of the gray wolf algorithm, such as easy premature maturity and low convergence accuracy, the four types of good point set initialization, convergence factor exponential decay, mutation and heuristic parameter determination are introduced on the premise of retaining fewer adjustable parameters. The simulation example verifies the feasibility and superiority of the model under two-phase and three-phase faults. We discuss the influence of the time level difference on the setting and the direction of future algorithm optimization and engineering application. This provides research ideas for the protection setting optimization problem of large-scale DG access to the distribution network. This work is supported by the Science and Technology Project of China Southern Power Grid Co., Ltd. (No. ZBKJXM20180057).